Data Mining Practical Machine Learning Tools and Techniques

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

I read this book the same weekend that the Packers took on the Rams, and the experience of the latter event, obviously, colored my judgment. Although I abhor anything that smacks of being a handbook (like, \"How to Earn a Merit Badge in Neurosurgery\") because too many volumes in biomedical science already evince a boyscout-like approach, I must confess that parts of this volume are fast, scholarly, and significant, with certain reservations. I like parts of this well-illustrated book because Dr. Sj6strand, without so stating, develops certain subjects on technique in relation to the acquisition of judgment and sophistication. And this is important! So, given that the author (like all of us) is somewhat deficient in some areas, and biased in others, the book is still valuable if the uninitiated reader swallows it in a general fashion, realizing full well that what will be required from the reader is a modulation to fit his vision, propreception, adaptation and response, and the kind of problem he is undertaking. A major deficiency of this book is revealed by comparison of its use of physics and of chemistry to provide understanding and background for the application of high resolution electron microscopy to problems in biology. Since the volume is keyed to high resolution electron microscopy, which is a sophisticated form of structural analysis, but really morphology in a modern guise, the physical and mechanical background of The instrument and its ancillary tools are simply and well presented. The potential use of chemical or cytochemical information as it relates to biological fine structure , however, is quite deficient. I wonder when even sophisticated morphol-ogists will consider fixation a reaction and not a technique; only then will the fundamentals become self-evident and predictable and this sine qua flon will become less mystical. Staining reactions (the most inadequate chapter) ought to be something more than a technique to selectively enhance contrast of morphological elements; it ought to give the structural addresses of some of the chemical residents of cell components. Is it pertinent that auto-radiography gets singled out for more complete coverage than other significant aspects of cytochemistry by a high resolution microscopist, when it has a built-in minimal error of 1,000 A in standard practice? I don't mean to blind-side (in strict football terminology) Dr. Sj6strand's efforts for what is \"routinely used in our laboratory\"; what is done is usually well done. It's just that …

Methods in Enzymology.

Implicit Solvation Models: Equilibria, Structure, Spectra, and Dynamics.

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

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Computational Methods in Drug Discovery

The interacting induced dipole polarization model implemented in our program for the calculation of molecular polarizabilities (POLAR) is used for the calculation of the molecular dipole-dipole polarizability ${\overline{\overline{α}}}$. POLAR is tested with Si$_{n}$, Ge$_{n}$ and Ga$_{n}$As$_{m}$ small clusters. The polarizability is an important quantity for the identification of clusters with different numbers of atoms and even for the separation of isomers. The results for the polarizability are in agreement with reference calculations performed with our version of the program PAPID (polarisabilites atomiques par interactions dipolaires) and with reference computations from Dr. J.R. Chelikowsky. The bulk limit for the polarizability is estimated from the Clausius-Mossotti relationship. The polarizability trend for the clusters as a function of size is different from what one might have expected. The clusters are more polarizable than what one might have inferred from the bulk polarizability. Previous experimental work yielded the opposite trend for somewhat larger clusters. At present, the origin of this difference is problematic. One might argue that smaller clusters need not behave like those of intermediate size. The high polarizability of small clusters is attributed to dangling bonds at the surface of the cluster. Indeed, most of the atoms within small clusters reside on the surface. In this respect, semiconductor clusters resemble metallic clusters.

Molecular polarizability of Si/Ge/GaAs semiconductors clusters

The interacting induced dipole polarization model implemented in our program POLAR is used for the calculation of the dipole-dipole polarizability alpha. The method is tested with single-wall carbon nanotube models as a function of nanotube radius and elliptical deformation. The results for polarizability follow the same trend as reference calculations performed with our version of the program PAPID. For the zigzag tubes, the polarizability is found to follow a remarkably simple law, that is, it varies as the inverse of the radius. A dramatic effect is also found with elliptical deformation. It is found that the polarizability and related properties can be modified continuously and reversibly by the external radial deformation. These results suggest an interesting technology in which mechanical deformation can control chemical properties of the carbon nanotubes. POLAR calculations differentiate more effectively than PAPID computations among single-wall nanotube models with increasing radial deformation. Different effective polarizabilities are calculated for the atoms at the highest and lowest curvature sites. POLAR calculations discriminate more efficiently than PAPID computations between the effective polarizabilities of the highest and lowest curvature sites. This remarkable and significant tunable polarizability can have important implications for metal coverage of metals on nanotubes and selective adsorption and desorption of foreign atoms and molecules on nanotubes and can lead to a wide variety of technological applications, such as catalysts, hydrogen storage, magnetic tubes, etc.

Effect of elliptical deformation on molecular polarizabilities of model carbon nanotubes from atomic increments.

Bundlet Model of Single- Wall Carbon, BC2N and BN Nanotubes, Cones and Horns in Organic Solvents
The existence of Single-wall C-nanocones (SWNCs), especially nanohorns (SWNHs) and BC2N/Boron Nitride (BN) analogues is discussed in organic solvents in cluster form. A theory is developed based on the bundlet model, describing distribution function by size. The phenomena present unified explanation in the model, in which free energy of (BC2N/BN )SWNCs involved in cluster, is combined from two components: volume one proportional to the number of molecules n in cluster and surface one, to n1/2. The model enables describing distribution function of (BC2N/BN )SWNC clusters by size. From geometrical differences, bundlet [(BC2N/BN )SWNCs]/ droplet (C60/B15C30N15/B30N30) models predict dissimilar behaviours. Various disclination (BC2N/BN )SWNCs are studied via energetic/ structural analyses. Several (BC2N/BN )SWNC’s ends are studied, which are different because of closing structure and arrangement type. Packing efficiencies and interaction-energy parameters of (BC2N/BN )SWNCs/SWNHs are intermediate between C60/ B15C30N15/B30N30 and (BC2N/BN )Single-wall C-nanotube (SWNT) clusters: in between behaviour is expected; however, properties of (BC2N/BN )SWNCs, especially (BC2N/BN )SWNHs, are calculated closer to (BC2N/BN )SWNTs. Structural asymmetry in different (BC2N/BN )SWNCs, characterized by cone angle, distinguishes properties of types: P2. BC2N/BN, especially species isoelectronic with C-analogues, may be stable.

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Bundlet Model of Single- Wall Carbon, BC2N and BN Nanotubes, Cones and Horns in Organic Solvents

The problem in this work is the computational characterization of cyclodextrins, crown ethers and hyaluronan (HA) as hosts of inclusion complexes for nanosized drug delivery vehicles in pharmaceutical formulations. The difficulty is addressed through a computational study of some thermodynamic, geometric and topological properties of the hosts. The calculated properties of oligosaccharides of D-glucopyranoses allow these to act as co-solvents of polyanions in water. In crown ethers, the central channel is computed. Mucoadhesive polymer HA in formulations releases drugs in mucosas. Geometric, topological and fractal analyses are carried out with code TOPO. Reference calculations are performed with code GEPOL. From HA to HA·3Ca and hydrate, the hydrophilic solvent-accessible surface varies with the count of H-bonds. The fractal dimension rises. The dimension of external atoms rises resulting 1.725 for HA. It rises going to HA·3Ca and hydrate. Nonburied minus molecular dimension rises and decays. Hydrate globularity is lower than O(water), Ca(2+) and O(HA). Ca(2+) rugosity is smaller than for hydrate, O(HA) and O(water). Ca(2+) and O(water) accessibilities are greater than hydrate. Conclusions are drawn on: (1) the relative stability of linear/cyclic and shorter/larger polymers; (2) the atomic analysis of properties allows determining the atoms with maximum reactivity.

Computational Study of Nanosized Drug Delivery from Cyclodextrins, Crown Ethers and Hyaluronan in Pharmaceutical Formulations.

Motivation. Novel carbon allotropes, with finite molecular structure, including spherical fullerenes are nowadays currently produced and investigated. These compounds have beautiful architectures and show unusual properties that are very promising for the development of nanotechnologies. The Kekule structure count and permanent of the adjacency matrix are computed for these molecules. Method. A method for computation of the permanent of the adjacency matrix is herein optimized for fullerenes. The method finds exact values for permanents of adjacency matrices up to 60u60. Results. The results provide linear and non–linear correlations between different structural parameters involving the presence of contiguous pentagons, ln[per(A)]/ln K, ln K and ln[per(A)]. Conclusions. A method for computing the permanent of the adjacency matrix is optimized for fullerenes. As ln[per(A)]/ln K can be related with thermodynamic stability, this aspect of chemistry could be useful for designing or predicting unknown fullerenes and their structure. The non–linear correlation for ln[per(A)]/ln K is improved. The variance decreases 49% and the risk of co–linearity diminishes. Availability. The software programs are available on request from the author (Francisco.Torrens@uv.es) and are free for academics.

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Francisco Torrens

Papers

Molecular polarizability of Si/Ge/GaAs semiconductors clusters

Effect of elliptical deformation on molecular polarizabilities of model carbon nanotubes from atomic increments.

Bundlet Model of Single- Wall Carbon, BC2N and BN Nanotubes, Cones and Horns in Organic Solvents

Computational Study of Nanosized Drug Delivery from Cyclodextrins, Crown Ethers and Hyaluronan in Pharmaceutical Formulations.

Computing the Permanent of the Adjacency Matrix for Fullerenes